1. Experiment Health for: Fragpipe LFQ

The experiment contains 12 samples; the condition of interest has 4 categories: control, recurrence, remission, ulcer.

A.Dimensionality reduction

The data have been log2 transformed and imputed using the MNAR imputation method before PCA.

PCA

MDS

B. Quantitative values CV distributions

2. Intensity distribution across runs

Imputed data

Initial data

3. Feature completedness

By sample

By protein

4. Imputed versus non imputed log2 Intensity values

5. Model QC

Volcano plots

MA plot

Histogram of pvalues

## $breaks
##  [1] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
## 
## $counts
##  [1] 204 162 139 118  78  70  78  48  56  46
## 
## $density
##  [1] 2.0420420 1.6216216 1.3913914 1.1811812 0.7807808 0.7007007 0.7807808 0.4804805 0.5605606 0.4604605
## 
## $mids
##  [1] 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95
## 
## $xname
## [1] "stats[, pval]"
## 
## $equidist
## [1] TRUE
## 
## attr(,"class")
## [1] "histogram"

## $breaks
##  [1] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
## 
## $counts
##  [1]  65  93  91 114  88 109  87 119 119 111
## 
## $density
##  [1] 0.6526104 0.9337349 0.9136546 1.1445783 0.8835341 1.0943775 0.8734940 1.1947791 1.1947791 1.1144578
## 
## $mids
##  [1] 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95
## 
## $xname
## [1] "stats[, pval]"
## 
## $equidist
## [1] TRUE
## 
## attr(,"class")
## [1] "histogram"

## $breaks
##  [1] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
## 
## $counts
##  [1] 142 101  89 102 120  91  85 102 106 104
## 
## $density
##  [1] 1.3627639 0.9692898 0.8541267 0.9788868 1.1516315 0.8733205 0.8157390 0.9788868 1.0172745 0.9980806
## 
## $mids
##  [1] 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95
## 
## $xname
## [1] "stats[, pval]"
## 
## $equidist
## [1] TRUE
## 
## attr(,"class")
## [1] "histogram"

## $breaks
##  [1] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
## 
## $counts
##  [1] 118 113 132 135 127  79  76  64  60  85
## 
## $density
##  [1] 1.1931244 1.1425683 1.3346815 1.3650152 1.2841254 0.7987867 0.7684530 0.6471183 0.6066734 0.8594540
## 
## $mids
##  [1] 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95
## 
## $xname
## [1] "stats[, pval]"
## 
## $equidist
## [1] TRUE
## 
## attr(,"class")
## [1] "histogram"

## $breaks
##  [1] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
## 
## $counts
##  [1] 337 230 128  83  70  46  49  41  37  32
## 
## $density
##  [1] 3.2003799 2.1842355 1.2155745 0.7882241 0.6647673 0.4368471 0.4653371 0.3893637 0.3513770 0.3038936
## 
## $mids
##  [1] 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95
## 
## $xname
## [1] "stats[, pval]"
## 
## $equidist
## [1] TRUE
## 
## attr(,"class")
## [1] "histogram"

## $breaks
##  [1] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
## 
## $counts
##  [1] 224  89  81  95  91  73  90 103  97  96
## 
## $density
##  [1] 2.1559192 0.8565929 0.7795958 0.9143407 0.8758422 0.7025987 0.8662175 0.9913378 0.9335900 0.9239654
## 
## $mids
##  [1] 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95
## 
## $xname
## [1] "stats[, pval]"
## 
## $equidist
## [1] TRUE
## 
## attr(,"class")
## [1] "histogram"